Ensured nodata is replaced with 255 in all level4 plugins

odc/stats/plugins/l34_utils/l4_bare_gradation.py

@@ -7,15 +7,23 @@
 
 def bare_gradation(xx: xr.Dataset, bare_threshold, veg_cover):
 
+    bs_pc_50 = expr_eval(
+        "where((a!=a), nodata, a)",
+        {"a": xx.bs_pc_50.data},
+        name="mark_veg",
+        dtype="float32",
+        **{"nodata": NODATA},
+    )
+
     # Map any data > 100 ---> 100
     bs_pc_50 = expr_eval(
         "where((a>100)&(a!=nodata), 100, a)",
-        {"a": xx.bs_pc_50.data},
+        {"a": bs_pc_50},
         name="mark_veg",
         dtype="uint8",
         **{"nodata": NODATA},
     )
-
+    
     # 60% <= data  --> 15
     bs_mask = expr_eval(
         "where((a>=m)&(a!=nodata), 15, a)",

odc/stats/plugins/l34_utils/l4_veg_cover.py

@@ -15,7 +15,7 @@ def canopyco_veg_con(xx: xr.Dataset, veg_threshold):
         dtype="float32",
         **{"nodata": NODATA},
     )
-
+    
     # Map any data > 100 ---> 100
     pv_pc_50 = expr_eval(
         "where((a>100) & (a!=nodata), 100, a)",
@@ -27,7 +27,7 @@ def canopyco_veg_con(xx: xr.Dataset, veg_threshold):
         **{"nodata": NODATA},
     )
 
-    # ## data < 1 ---> 0
+    # data < 1 ---> 0
     veg_mask = expr_eval(
         "where(a<m, 0, a)",
         {

odc/stats/plugins/l34_utils/l4_water.py

@@ -7,7 +7,7 @@ def water_classification(xx, intertidal_mask, water_persistence):
 
     l4 = expr_eval(
         "where(((a==223)|(a==221))&(b==1), 101, a)",
-        {"a": xx.classes_l3_l4.data, "b": water_persistence},
+        {"a": xx.level_3_4.data, "b": water_persistence},
         name="mark_water",
         dtype="uint8",
     )

odc/stats/plugins/l34_utils/l4_water_persistence.py

@@ -7,18 +7,14 @@
 
 
 def water_persistence(xx: xr.Dataset, watper_threshold):
-
-    # Apply nodata
+ 
+    # Address nan
     water_frequency = expr_eval(
-        "where((a==water_freq_nodata), nodata, a)",
+        "where((a!=a), nodata, a)",
         {"a": xx.water_frequency.data},
         name="mark_water",
-        dtype="uint8",
-        **{
-            "m": watper_threshold[3],
-            "nodata": NODATA,
-            "water_freq_nodata": WATER_FREQ_NODATA,
-        },
+        dtype="float32",
+        **{"nodata": NODATA},
     )
 
     #  10 <= water_frequency < 1 --> 1

odc/stats/plugins/l34_utils/lc_intertidal_mask.py

@@ -9,7 +9,7 @@ def intertidal_mask(xx: xr.Dataset):
 
     res = expr_eval(
         "where(a==_u, 1, 0)",
-        {"a": xx.classes_l3_l4.data},
+        {"a": xx.level_3_4.data},
         name="mask_intertidal",
         dtype="uint8",
         **{"_u": 223},

odc/stats/plugins/l34_utils/lc_level3.py

@@ -14,7 +14,7 @@ def lc_level3(xx: xr.Dataset):
 
     res = expr_eval(
         "where((a!=a)|(a>=nodata), b, a)",
-        {"a": xx.cultivated.data, "b": xx.classes_l3_l4.data},
+        {"a": xx.cultivated.data, "b": xx.level_3_4.data},
         name="mask_cultivated",
         dtype="float32",
         **{"nodata": xx.cultivated.attrs.get("nodata")},
@@ -46,7 +46,7 @@ def lc_level3(xx: xr.Dataset):
     # Add intertidal as water
     res = expr_eval(
         "where((a==223)|(a==221), 220, b)",
-        {"a": xx.classes_l3_l4.data, "b": res},
+        {"a": xx.level_3_4.data, "b": res},
         name="mark_urban",
         dtype="uint8",
     )

odc/stats/plugins/l34_utils/lc_water_seasonality.py

@@ -2,21 +2,20 @@
 
 from odc.stats._algebra import expr_eval
 
-WATER_FREQ_NODATA = -999
 NODATA = 255
 
 
 def water_seasonality(xx: xr.Dataset, water_seasonality_threshold):
     # >= 3 months ----> 1  Semi-permanent or permanent
     # < 3 months  ----> 2 Temporary or seasonal
-
+    
     # Apply nodata
     water_frequency = expr_eval(
-        "where((a!=a)|(a==watersea_nodata), nodata, a)",
+        "where((a!=a), nodata, a)",
         {"a": xx.water_frequency.data},
         name="mark_water_season",
         dtype="float32",
-        **{"nodata": NODATA, "watersea_nodata": WATER_FREQ_NODATA},
+        **{"nodata": NODATA},
     )
 
     water_season_mask = expr_eval(

odc/stats/plugins/lc_level34.py

@@ -64,16 +64,16 @@ def reduce(self, xx: xr.Dataset) -> xr.Dataset:
         water_persistence = l4_water_persistence.water_persistence(
             xx, self.watper_threshold
         )
-
+        # print("### Water Persistence", np.unique(water_persistence.compute()))
         water_seasonality = lc_water_seasonality.water_seasonality(
             xx, self.water_seasonality_threshold
         )
-
+        # print("### Water Seasonality", np.unique(water_persistence.compute()))
         intertidal_mask = lc_intertidal_mask.intertidal_mask(xx)
 
         # #TODO WATER (99-104)
         l4 = l4_water.water_classification(xx, intertidal_mask, water_persistence)
-
+        # print("### Water classification", np.unique(water_persistence.compute()))
         # Generate Level3 classes
         level3 = lc_level3.lc_level3(xx)
 
@@ -93,7 +93,6 @@ def reduce(self, xx: xr.Dataset) -> xr.Dataset:
         bare_gradation = l4_bare_gradation.bare_gradation(
             xx, self.bare_threshold, veg_cover
         )
-
         l4 = l4_natural_aquatic.natural_auquatic_veg(l4, veg_cover, water_seasonality)
 
         level4 = l4_surface.lc_l4_surface(l4, level3, bare_gradation)
@@ -103,7 +102,7 @@ def reduce(self, xx: xr.Dataset) -> xr.Dataset:
 
         attrs = xx.attrs.copy()
         attrs["nodata"] = NODATA
-        dims = xx.classes_l3_l4.dims[1:]
+        dims = xx.level_3_4.dims[1:]
         data_vars = {
             k: xr.DataArray(v, dims=dims, attrs=attrs)
             for k, v in zip(self.measurements, [level3.squeeze(), level4.squeeze()])

tests/test_lc_l34.py

@@ -106,7 +106,7 @@ def image_groups():
     }
 
     data_vars = {
-        "classes_l3_l4": xr.DataArray(
+        "level_3_4": xr.DataArray(
             da.from_array(l34, chunks=(1, -1, -1)),
             dims=("spec", "y", "x"),
             attrs={"nodata": 255},

tests/test_lc_l4_ctv.py

@@ -27,7 +27,7 @@ def image_groups(l34, urban, cultivated, woody, pv_pc_50):
     }
 
     data_vars = {
-        "classes_l3_l4": xr.DataArray(
+        "level_3_4": xr.DataArray(
             da.from_array(l34, chunks=(1, -1, -1)),
             dims=("spec", "y", "x"),
             attrs={"nodata": 255},
@@ -135,7 +135,7 @@ def test_ctv_classes_woody():
     veg_cover = l4_veg_cover.canopyco_veg_con(xx, stats_l4.veg_threshold)
 
     l4_ctv = l4_cultivated.lc_l4_cultivated(
-        xx.classes_l3_l4, level3, lifeform, veg_cover
+        xx.level_3_4, level3, lifeform, veg_cover
     )
 
     assert (l4_ctv.compute() == expected_cultivated_classes).all()
@@ -217,7 +217,7 @@ def test_ctv_classes_herbaceous():
     veg_cover = l4_veg_cover.canopyco_veg_con(xx, stats_l4.veg_threshold)
 
     l4_ctv = l4_cultivated.lc_l4_cultivated(
-        xx.classes_l3_l4, level3, lifeform, veg_cover
+        xx.level_3_4, level3, lifeform, veg_cover
     )
     assert (l4_ctv.compute() == expected_cultivated_classes).all()
 
@@ -298,7 +298,7 @@ def test_ctv_classes_woody_herbaceous():
     veg_cover = l4_veg_cover.canopyco_veg_con(xx, stats_l4.veg_threshold)
 
     l4_ctv = l4_cultivated.lc_l4_cultivated(
-        xx.classes_l3_l4, level3, lifeform, veg_cover
+        xx.level_3_4, level3, lifeform, veg_cover
     )
 
     assert (l4_ctv.compute() == expected_cultivated_classes).all()
@@ -380,6 +380,6 @@ def test_ctv_classes_no_vegcover():
     veg_cover = l4_veg_cover.canopyco_veg_con(xx, stats_l4.veg_threshold)
 
     l4_ctv = l4_cultivated.lc_l4_cultivated(
-        xx.classes_l3_l4, level3, lifeform, veg_cover
+        xx.level_3_4, level3, lifeform, veg_cover
     )
     assert (l4_ctv.compute() == expected_cultivated_classes).all()

tests/test_lc_l4_natural_surface.py

@@ -36,7 +36,7 @@ def image_groups(l34, urban, woody, bs_pc_50, pv_pc_50, cultivated, water_freque
     }
 
     data_vars = {
-        "classes_l3_l4": xr.DataArray(
+        "level_3_4": xr.DataArray(
             da.from_array(l34, chunks=(1, -1, -1)),
             dims=("spec", "y", "x"),
             attrs={"nodata": 255},
@@ -180,7 +180,7 @@ def test_ns():
 
     # Apply cultivated to match the code in Level4 processing
     l4_ctv = l4_cultivated.lc_l4_cultivated(
-        xx.classes_l3_l4, level3, lifeform, veg_cover
+        xx.level_3_4, level3, lifeform, veg_cover
     )
     l4_ctv_ntv = l4_natural_veg.lc_l4_natural_veg(l4_ctv, level3, lifeform, veg_cover)
 

tests/test_lc_l4_nav.py

@@ -34,7 +34,7 @@ def image_groups(l34, urban, cultivated, woody, pv_pc_50, water_frequency):
     }
 
     data_vars = {
-        "classes_l3_l4": xr.DataArray(
+        "level_3_4": xr.DataArray(
             da.from_array(l34, chunks=(1, -1, -1)),
             dims=("spec", "y", "x"),
             attrs={"nodata": 255},
@@ -154,7 +154,7 @@ def test_ntv_classes_woody_herbaceous():
 
     # Apply cultivated to match the code in Level4 processing
     l4_ctv = l4_cultivated.lc_l4_cultivated(
-        xx.classes_l3_l4, level3, lifeform, veg_cover
+        xx.level_3_4, level3, lifeform, veg_cover
     )
     l4_ctv_ntv = l4_natural_veg.lc_l4_natural_veg(l4_ctv, level3, lifeform, veg_cover)
 
@@ -256,7 +256,7 @@ def test_ntv_herbaceous_seasonal_water_veg_cover():
 
     # Apply cultivated to match the code in Level4 processing
     l4_ctv = l4_cultivated.lc_l4_cultivated(
-        xx.classes_l3_l4, level3, lifeform, veg_cover
+        xx.level_3_4, level3, lifeform, veg_cover
     )
     l4_ctv_ntv = l4_natural_veg.lc_l4_natural_veg(l4_ctv, level3, lifeform, veg_cover)
 
@@ -358,7 +358,7 @@ def test_ntv_woody_seasonal_water_veg_cover():
 
     # Apply cultivated to match the code in Level4 processing
     l4_ctv = l4_cultivated.lc_l4_cultivated(
-        xx.classes_l3_l4, level3, lifeform, veg_cover
+        xx.level_3_4, level3, lifeform, veg_cover
     )
     l4_ctv_ntv = l4_natural_veg.lc_l4_natural_veg(l4_ctv, level3, lifeform, veg_cover)
 
@@ -455,7 +455,7 @@ def test_ntv_herbaceous_permanent_water_veg_cover():
 
     # Apply cultivated to match the code in Level4 processing
     l4_ctv = l4_cultivated.lc_l4_cultivated(
-        xx.classes_l3_l4, level3, lifeform, veg_cover
+        xx.level_3_4, level3, lifeform, veg_cover
     )
     l4_ctv_ntv = l4_natural_veg.lc_l4_natural_veg(l4_ctv, level3, lifeform, veg_cover)
 

tests/test_lc_l4_ntv.py

@@ -31,7 +31,7 @@ def image_groups(l34, urban, cultivated, woody, pv_pc_50):
     }
 
     data_vars = {
-        "classes_l3_l4": xr.DataArray(
+        "level_3_4": xr.DataArray(
             da.from_array(l34, chunks=(1, -1, -1)),
             dims=("spec", "y", "x"),
             attrs={"nodata": 255},
@@ -137,7 +137,7 @@ def test_ntv_classes_herbaceous():
     lifeform = lc_lifeform.lifeform(xx)
     veg_cover = l4_veg_cover.canopyco_veg_con(xx, stats_l4.veg_threshold)
     l4_ntv = l4_natural_veg.lc_l4_natural_veg(
-        xx.classes_l3_l4, level3, lifeform, veg_cover
+        xx.level_3_4, level3, lifeform, veg_cover
     )
     assert (l4_ntv.compute() == expected_natural_terrestrial_veg_classes).all()
 
@@ -218,7 +218,7 @@ def test_ntv_classes_woody():
     veg_cover = l4_veg_cover.canopyco_veg_con(xx, stats_l4.veg_threshold)
 
     l4_ntv = l4_natural_veg.lc_l4_natural_veg(
-        xx.classes_l3_l4, level3, lifeform, veg_cover
+        xx.level_3_4, level3, lifeform, veg_cover
     )
     assert (l4_ntv.compute() == expected_natural_terrestrial_veg_classes).all()
 
@@ -298,7 +298,7 @@ def test_ntv_classes_no_veg():
     lifeform = lc_lifeform.lifeform(xx)
     veg_cover = l4_veg_cover.canopyco_veg_con(xx, stats_l4.veg_threshold)
     l4_ntv = l4_natural_veg.lc_l4_natural_veg(
-        xx.classes_l3_l4, level3, lifeform, veg_cover
+        xx.level_3_4, level3, lifeform, veg_cover
     )
     assert (l4_ntv.compute() == expected_natural_terrestrial_veg_classes).all()
 
@@ -378,6 +378,6 @@ def test_ntv_classes_no_lifeform():
     lifeform = lc_lifeform.lifeform(xx)
     veg_cover = l4_veg_cover.canopyco_veg_con(xx, stats_l4.veg_threshold)
     l4_ntv = l4_natural_veg.lc_l4_natural_veg(
-        xx.classes_l3_l4, level3, lifeform, veg_cover
+        xx.level_3_4, level3, lifeform, veg_cover
     )
     assert (l4_ntv.compute() == expected_natural_terrestrial_veg_classes).all()

tests/test_lc_l4_water.py

@@ -32,7 +32,7 @@ def image_groups(l34, urban, cultivated, woody, bs_pc_50, pv_pc_50, water_freque
     }
 
     data_vars = {
-        "classes_l3_l4": xr.DataArray(
+        "level_3_4": xr.DataArray(
             da.from_array(l34, chunks=(1, -1, -1)),
             dims=("spec", "y", "x"),
             attrs={"nodata": 255},

tests/test_lc_level3.py

@@ -64,7 +64,7 @@ def image_groups():
     }
 
     data_vars = {
-        "classes_l3_l4": xr.DataArray(
+        "level_3_4": xr.DataArray(
             da.from_array(l34, chunks=(1, -1, -1)),
             dims=("spec", "y", "x"),
             attrs={"nodata": 255},